795 resultados para time-varying AR models


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A reconstruction of the Atlantic Meridional Overturning Circulation (MOC) for the period 1959–2006 has been derived from the ECMWF operational ocean reanalysis. The reconstruction shows a wide range of time-variability, including a downward trend. At 26N, both the MOC intensity and changes in its vertical structure are in good agreement with previous estimates based on trans-Atlantic surveys. At 50N, the MOC and strength of the subpolar gyre are correlated at interannual time scales, but show opposite secular trends. Heat transport variability is highly correlated with the MOC but shows a smaller trend due to the warming of the upper ocean, which partially compensates for the weakening of the circulation. Results from sensitivity experiments show that although the time-varying upper boundary forcing provides useful MOC information, the sequential assimilation of ocean data further improves the MOC estimation by increasing both the mean and the time variability.

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We consider the imposition of Dirichlet boundary conditions in the finite element modelling of moving boundary problems in one and two dimensions for which the total mass is prescribed. A modification of the standard linear finite element test space allows the boundary conditions to be imposed strongly whilst simultaneously conserving a discrete mass. The validity of the technique is assessed for a specific moving mesh finite element method, although the approach is more general. Numerical comparisons are carried out for mass-conserving solutions of the porous medium equation with Dirichlet boundary conditions and for a moving boundary problem with a source term and time-varying mass.

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We investigated diurnal nitrate (NO3-) concentration variability in the San Joaquin River using an in situ optical NO3- sensor and discrete sampling during a 5-day summer period characterized by high algal productivity. Dual NO3- isotopes (delta N-15(NO3) and delta O-18(NO3)) and dissolved oxygen isotopes (delta O-18(DO)) were measured over 2 days to assess NO3- sources and biogeochemical controls over diurnal time-scales. Concerted temporal patterns of dissolved oxygen (DO) concentrations and delta O-18(DO) were consistent with photosynthesis, respiration and atmospheric O-2 exchange, providing evidence of diurnal biological processes independent of river discharge. Surface water NO3- concentrations varied by up to 22% over a single diurnal cycle and up to 31% over the 5-day study, but did not reveal concerted diurnal patterns at a frequency comparable to DO concentrations. The decoupling of delta N-15(NO3) and delta O-18(NO3) isotopes suggests that algal assimilation and denitrification are not major processes controlling diurnal NO3- variability in the San Joaquin River during the study. The lack of a clear explanation for NO3- variability likely reflects a combination of riverine biological processes and time-varying physical transport of NO3- from upstream agricultural drains to the mainstem San Joaquin River. The application of an in situ optical NO3- sensor along with discrete samples provides a view into the fine temporal structure of hydrochemical data and may allow for greater accuracy in pollution assessment.

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In most climate simulations used by the Intergovernmental Panel on Climate Change 2007 fourth assessment report, stratospheric processes are only poorly represented. For example, climatological or simple specifications of time-varying ozone concentrations are imposed and the quasi-biennial oscillation (QBO) of equatorial stratospheric zonal wind is absent. Here we investigate the impact of an improved stratospheric representation using two sets of perturbed simulations with the Hadley Centre coupled ocean atmosphere model HadGEM1 with natural and anthropogenic forcings for the 1979–2003 period. In the first set of simulations, the usual zonal mean ozone climatology with superimposed trends is replaced with a time series of observed zonal mean ozone distributions that includes interannual variability associated with the solar cycle, QBO and volcanic eruptions. In addition to this, the second set of perturbed simulations includes a scheme in which the stratospheric zonal wind in the tropics is relaxed to appropriate zonal mean values obtained from the ERA-40 re-analysis, thus forcing a QBO. Both of these changes are applied strictly to the stratosphere only. The improved ozone field results in an improved simulation of the stepwise temperature transitions observed in the lower stratosphere in the aftermath of the two major recent volcanic eruptions. The contribution of the solar cycle signal in the ozone field to this improved representation of the stepwise cooling is discussed. The improved ozone field and also the QBO result in an improved simulation of observed trends, both globally and at tropical latitudes. The Eulerian upwelling in the lower stratosphere in the equatorial region is enhanced by the improved ozone field and is affected by the QBO relaxation, yet neither induces a significant change in the upwelling trend.

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The near-Earth heliospheric magnetic field intensity, |B|, exhibits a strong solar cycle variation, but returns to the same ``floor'' value each solar minimum. The current minimum, however, has seen |B| drop below previous minima, bringing in to question the existence of a floor, or at the very least requiring a re-assessment of its value. In this study we assume heliospheric flux consists of a constant open flux component and a time-varying contribution from CMEs. In this scenario, the true floor is |B| with zero CME contribution. Using observed CME rates over the solar cycle, we estimate the ``no-CME'' |B| floor at ~4.0 +/- 0.3 nT, lower than previous floor estimates and below |B| observed this solar minimum. We speculate that the drop in |B| observed this minimum may be due to a persistently lower CME rate than the previous minimum, though there are large uncertainties in the supporting observational data.

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Counterstreaming electrons (CSEs) are treated as signatures of closed magnetic flux, i.e., loops connected to the Sun at both ends. However, CSEs at 1 AU likely fade as the apex of a closed loop passes beyond some distance R, owing to scattering of the sunward beam along its continually increasing path length. The remaining antisunward beam at 1 AU would then give a false signature of open flux. Subsequent opening of a loop at the Sun by interchange reconnection with an open field line would produce an electron dropout (ED) at 1 AU, as if two open field lines were reconnecting to completely disconnect from the Sun. Thus EDs can be signatures of interchange reconnection as well as the commonly attributed disconnection. We incorporate CSE fadeout into a model that matches time-varying closed flux from interplanetary coronal mass ejections (ICMEs) to the solar cycle variation in heliospheric flux. Using the observed occurrence rate of CSEs at solar maximum, the model estimates R ∼ 8–10 AU. Hence we demonstrate that EDs should be much rarer than CSEs at 1 AU, as EDs can only be detected when the juncture points of reconnected field lines lie sunward of the detector, whereas CSEs continue to be detected in the legs of all loops that have expanded beyond the detector, out to R. We also demonstrate that if closed flux added to the heliosphere by ICMEs is instead balanced by disconnection elsewhere, then ED occurrence at 1 AU would still be rare, contrary to earlier expectations.

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An adaptive tuned vibration absorber (ATVA) with a smart variable stiffness element is capable of retuning itself in response to a time-varying excitation frequency., enabling effective vibration control over a range of frequencies. This paper discusses novel methods of achieving variable stiffness in an ATVA by changing shape, as inspired by biological paradigms. It is shown that considerable variation in the tuned frequency can be achieved by actuating a shape change, provided that this is within the limits of the actuator. A feasible design for such an ATVA is one in which the device offers low resistance to the required shape change actuation while not being restricted to low values of the effective stiffness of the vibration absorber. Three such original designs are identified: (i) A pinned-pinned arch beam with fixed profile of slight curvature and variable preload through an adjustable natural curvature; (ii) a vibration absorber with a stiffness element formed from parallel curved beams of adjustable curvature vibrating longitudinally; (iii) a vibration absorber with a variable geometry linkage as stiffness element. The experimental results from demonstrators based on two of these designs show good correlation with the theory.

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Optical density measurements were used to estimate the effect of heat treatments on the single-cell lag times of Listeria innocua fitted to a shifted gamma distribution. The single-cell lag time was subdivided into repair time ( the shift of the distribution assumed to be uniform for all cells) and adjustment time (varying randomly from cell to cell). After heat treatments in which all of the cells recovered (sublethal), the repair time and the mean and the variance of the single-cell adjustment time increased with the severity of the treatment. When the heat treatments resulted in a loss of viability (lethal), the repair time of the survivors increased with the decimal reduction of the cell numbers independently of the temperature, while the mean and variance of the single-cell adjustment times remained the same irrespective of the heat treatment. Based on these observations and modeling of the effect of time and temperature of the heat treatment, we propose that the severity of a heat treatment can be characterized by the repair time of the cells whether the heat treatment is lethal or not, an extension of the F value concept for sublethal heat treatments. In addition, the repair time could be interpreted as the extent or degree of injury with a multiple-hit lethality model. Another implication of these results is that the distribution of the time for cells to reach unacceptable numbers in food is not affected by the time-temperature combination resulting in a given decimal reduction.

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A mathematical growth model for the batch solid-state fermentation process for fungal tannase production was developed and tested experimentally. The unstructured model describes the uptake and growth kinetics of Penicillium glabrum in an impregnated polyurethane foam substrate system. In general, good agreement between the experimental data and model simulations was obtained. Biomass, tannase and spore production are described by logistic kinetics with a time delay between biomass production and tannase and spore formation. Possible induction mechanisms for the latter are proposed. Hydrolysis of tannic acid, the main carbon source in the substrate system, is reasonably well described with Michaelis-Menten kinetics with time-varying enzyme concentration but a more complex reaction mechanism is suspected. The metabolism of gallic acid, a tannase-hydrolysis product of tannic acid, was shown to be growth limiting during the main growth phase. (c) 2004 Elsevier Ltd. All rights reserved.

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Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.

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The recursive least-squares algorithm with a forgetting factor has been extensively applied and studied for the on-line parameter estimation of linear dynamic systems. This paper explores the use of genetic algorithms to improve the performance of the recursive least-squares algorithm in the parameter estimation of time-varying systems. Simulation results show that the hybrid recursive algorithm (GARLS), combining recursive least-squares with genetic algorithms, can achieve better results than the standard recursive least-squares algorithm using only a forgetting factor.

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A discrete-time algorithm is presented which is based on a predictive control scheme in the form of dynamic matrix control. A set of control inputs are calculated and made available at each time instant, the actual input applied being a weighted summation of the inputs within the set. The algorithm is directly applicable in a self-tuning format and is therefore suitable for slowly time-varying systems in a noisy environment.

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The tap-length, or the number of the taps, is an important structural parameter of the linear MMSE adaptive filter. Although the optimum tap-length that balances performance and complexity varies with scenarios, most current adaptive filters fix the tap-length at some compromise value, making them inefficient to implement especially in time-varying scenarios. A novel gradient search based variable tap-length algorithm is proposed, using the concept of the pseudo-fractional tap-length, and it is shown that the new algorithm can converge to the optimum tap-length in the mean. Results of computer simulations are also provided to verify the analysis.

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This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student’s t-density and consequently can be estimated simply using maximum likelihood. The method is applied to a set of four daily financial asset return series comprising U.S. and U.K. stocks and bonds, and significant evidence in favor of the presence of autoregressive conditional kurtosis is observed. Various extensions to the basic model are proposed, and we show that the response of kurtosis to good and bad news is not significantly asymmetric.

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This paper investigates the time series behaviour of the relative benefits of sector and regional diversification strategies, using the notion of cross-sectional dispersion introduced by Solnik and Roulet (2000). Using monthly data over the period 1987:1 to 2002:12, four sector and four regional classifications are examined in the UK. The results indicate that sector and regional dispersion indices are highly time varying and so dwarf any lower frequency cyclical components that may be present. Nonetheless, periods of high dispersion are closely followed by periods of low dispersion, suggestive of cyclical behaviour of sector and regional diversification benefits. Then, using the HP-filter we isolated the cyclical component of the various dispersion indices and found that the sector dispersion indices are generally above the regional dispersion indices. This implies that a sector diversification strategy is likely to offer greater risk reduction benefits than a regional diversification approach. Nonetheless, we find that in some periods, certain regional diversification strategies are of equal or greater benefit than certain sector approaches. The results also appear to be quite sensitive to the classifications of sectors and regions. Hence, the appropriate definition of sectors and regions can have important implications for sector and regional diversification strategies.